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JAIDS Journal of Acquired Immune Deficiency Syndromes:
doi: 10.1097/QAI.0b013e318141f965
Epidemiology and Social Science

Gender Differences in Sex Risk Behaviors Among Ukraine Injection Drug Users

Booth, Robert E PhD, MA*; Lehman, Wayne E PhD*; Brewster, John T LCSW*; Sinitsyna, Larisa MA†; Dvoryak, Sergey MD, PhD‡

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Author Information

From the *Department of Psychiatry, University of Colorado Health Sciences Center, Denver, CO; †Counterpart International, Kiev, Ukraine; and ‡Ukrainian Institute on Public Health Policy, Kiev, Ukraine.

Received for publication February 15, 2007; accepted June 14, 2007.

Sponsored by the National Institute on Drug Abuse (grant DA09832).

Reprints: Robert E. Booth, PhD, University of Colorado Health Sciences Center, 1741 Vine Street, Denver, CO 80206 (e-mail: robert.booth@UCHSC.edu).

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Abstract

Objective: To assess gender differences in drug and sex risk behaviors and evaluate predictors of HIV-related sex risk behaviors among heterosexual injection drug users (IDUs) in Ukraine.

Design: Street-recruited IDUs from Kiev, Odessa, and Makeevka/Donesk, Ukraine.

Methods: From June 2004 through November 2006, outreach workers recruited 1557 IDUs, including 526 from Kiev, 494 from Odessa, and 537 from Makeevka/Donesk. Participants were administered a standardized computer-assisted interview assessing HIV-related drug and sex risk behaviors, self-efficacy for practicing safe sex, and HIV knowledge.

Results: Overall, 80% of the participants were sexually active in the 30-day period before their interview. They also engaged in high-risk sex behaviors during this brief 30-day window: 53% reported anal or vaginal sex without a condom, 27% had sex with more than 1 partner, 41% had an IDU sex partner, and 37% had an HIV-positive sex partner or a partner whose HIV status they did not know. Overall, women were at higher risk than men and were more likely to have been told they were HIV-positive.

Conclusion: The extremely high HIV prevalence rate in Ukraine and in this cohort, combined with their recent high-risk sex behaviors, forecasts not only a continuance of the epidemic in the region but an escalation.

Ukraine is presently at the epicenter of HIV in Europe, with an estimated prevalence of nearly 500,000, or 1.5%, of the adult population.1 Yet, as late as 1994, the World Health Organization (WHO) estimated that there were only 1500 cases of HIV in Ukraine, attributable mainly to heterosexual transmission,2 and in 1995, the WHO characterized Ukraine as a low-prevalence country.3 The sharp rise in HIV after this period was fueled by injection drug users (IDUs), as initially reported in 2 cities in southern Ukraine, Odessa and Nikolaev.4,5

The HIV epidemic in Ukraine continues to grow at an alarming rate, with annual diagnoses more than doubling each year since 2000 and the number of registered HIV infections among IDUs increasing by 34% in 2005 compared with 2003.6 By 2010, some officials believe there may be as many as 1.5 million infections.4 This perception is attributable largely to an increase in sexually transmitted infections among non-drug injectors. From 1999 through 2003 to the first 6 months of 2006, the proportion of individuals infected through heterosexual transmission increased from 14% of all new cases to 35%, including 41% among women (Ukranian AIDS Centre, unpublished data, 2006). In Donetsk and Odessa, 2 of the 3 cities included in this study, 55% to 60% of new infections were attributable to unprotected sex with an infected IDU partner.7

The present investigation was designed to assess gender differences in drug and sex risks among heterosexual IDUs in Ukraine, with particular emphasis on predictors of HIV-related sex risk behaviors. To our knowledge, this is the first assessment focusing on gender differences in sex risks among IDUs in Ukraine. Based on earlier work, it was hypothesized that women would be more likely than men to report having unprotected anal or vaginal sex8,9 and sex with a high-risk partner,10 including an IDU sex partner,11-13 an HIV-infected sex partner,8 or a partner of unknown HIV status.9 We were uncertain concerning differences in multiple sex partners. Using data from 8 US sites, we recently reported that women were twice as likely as men to have had more than 1 sex partner in the past 30 days;14 however, others have not found the same.15

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METHODS

From June 2004 through November 2006, 1557 IDU participants were recruited, including 526 from Kiev, 494 from Odessa, and 537 from Makeevka/Donesk. Makeevka and Donesk are 2 cities adjacent to each other in the Donesk oblast or region. Recruitment was conducted by former drug injectors working for nongovernmental organizations (NGOs) using strategies based on the Indigenous Leader Outreach Model (ILOM).16 Our experience, and that of others, supports indigenous outreach workers serving in this capacity.17,18 Areas were targeted for participant recruitment based on staff members' knowledge of where IDUs congregated.

Eligibility included self-reporting injecting drugs in the past 30 days, being 18 years of age or older, not being too intoxicated or otherwise incapacitated to comprehend and provide informed consent, and agreeing to be interviewed for approximately 1 hour and tested for HIV. Drug injection was verified through visual inspection for signs of recent venipuncture. Outreach workers initially assessed eligibility on the street, with final determination made by the NGOs' interviewers. After the interview, participants were tested for HIV using the HIV I + II One-Step Test finger-stick rapid HIV test (Orgenics Ltd, Yavne, Israel). Participants were compensated the equivalent of US $5 for their time. All study procedures were approved by the Institutional Review Board (IRB) of the University of Colorado Health Sciences Center, which served as the IRB of record through a Federal-Wide Assurance of Protection for Human Subjects, because there was no in-country IRB when the study began.

Interviews were conducted using an audio-computer-administered self-interview (ACASI) by staff comfortable in working with IDUs. The primary study measure was slightly modified from the Risk Behavior Assessment (RBA) developed during the National Institute on Drug Abuse's Cooperative Agreement in the 1990s, based on focus groups with IDUs in Ukraine conducted by the first author19 and on reviews by colleagues in Ukraine. Reliability and validity assessments of the RBA support its use for research with IDUs.20,21 In addition, we measured self-efficacy for engaging in safer sex behaviors and HIV knowledge. Self-efficacy was assessed using the Behaviors and Beliefs Trailer form developed in the Cooperative Agreement by Dr. Fen Rhodes. HIV knowledge was based on a measure developed by Carey et al.22 All instruments were translated by an IRB-certified Russian translator in Denver.

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Statistical Analyses

Four high-risk sex behaviors were examined, including the following: (1) having sex with multiple partners (ie, 2 or more), (2) having vaginal or anal sex at least once without using a condom, (3) having sex with a partner who was known to be an IDU, and (4) having sex with a partner who was HIV-positive or not knowing the HIV status of the partner. The risk window focused on the 30-day period before the interview.

Men and women were first compared with each other on key variables to be used in subsequent analyses. Gender differences in mean age, total times injected, self-efficacy, and HIV knowledge were assessed through t tests. Univariate associations for categoric variables were estimated using χ2 tests. After these initial analyses, multiple logistic regressions were fitted to the data to assess the independent contribution of predictor variables with each of the 4 sex risk-dependent measures. Logistic regressions were performed on the combined sample of male and female participants, with gender included as a predictor. Codes for city (Kiev and Odessa) were included to control for differences between sites. Adjusted odds ratios (ORs) and 95% confidence intervals (CIs) were calculated from the logistic regression coefficients to assess associations between predictor and dependent variables. A standard statistical software package was used for all analyses.23

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RESULTS

Drug use patterns and HIV-positive rates differed significantly between the 3 cities. Kiev and Makeevka/Donesk included a mix of stimulant injectors (35% and 41%, respectively), opiate injectors (44% and 35%, respectively), and opiate/sedative mix injectors (21% and 23%, respectively). Most IDUs in Odessa, however, were opiate injectors (62% vs. 13% for stimulants and 25% for opiates/sedatives). HIV-positive serology results also differed between the cities, with 51% of those from Odessa testing positive for HIV compared with 34% for Kiev and 17% for Makeevka/Donesk. Overall, only 36% had previously been told that they were infected with HIV. Because of these differences, codes to control for city were included in the multiple logistic regressions.

Sample characteristics by gender for the 1557 participants are shown in Table 1. The study population included 1182 men (76%) and 375 women (24%). They averaged 29 years of age (SD = 7.7), and 30% were married or living as married. Women were more likely to have been married than men (40% and 27%, respectively; χ2 = 23.88, df = 1; P < 0.001). Nearly 31% reported having had a sexually transmitted disease (STD) in the past, and 13% had been told that they were HIV-positive, with a higher percentage of women positive than men (17% vs. 12%, respectively; χ2 = 6.45, df = 1; P < 0.05). According to drug of choice, women were more likely than men to favor stimulants (36% and 28%, respectively), whereas men favored opiates (48% and 43%, respectively) and opiates/sedatives (24% and 21%, respectively; χ2 = 8.85, df = 2; P < 0.05). There were no significant gender differences on needle risks, although men and women were at high risk. In terms of self-efficacy, women had higher scores (and thus greater self-efficacy) than men (mean = 2.7 and 2.5, respectively; t = 6.77, df = 700; P < 0.001). Respondents correctly answered an average of 67% of the questions on the HIV knowledge test.

Table 1
Table 1
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Overall, 81% of men and 80% of women were sexually active in the 30 days before their interview, with an average 1.57 sex partners for each gender. High-risk sex behaviors according to gender are shown in Table 2. Sex with more than 1 partner was reported by 27%, 53% had vaginal or anal sex without using a condom, 41% had sex with a partner who was an IDU, and 37% had sex with a partner who was HIV-positive or whose status was unknown. Men were twice as likely as women to have had more than 1 sex partner in the past 30 days (30% and 15%, respectively; χ2 = 33.42, df = 1; P < 0.001), whereas women were nearly twice as likely as men to have had sex with an IDU (65% and 34%, respectively; χ2 = 111.74, df = 1; P < 0.001).

Table 2
Table 2
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Univariate Analyses of Sex Risk Behaviors

Univariate analyses were conducted for each predictor variable by each of the 4 high-risk sex behaviors (tables not shown). Those who had multiple sexual partners in the past 30 days were more likely to be male (χ2 = 33.42, df = 1; P < 0.001), to be younger (t = 3.19, df = 790; P < 0.01), not to be living as married (χ2 = 52.51, df = 1; P < 0.001), to have reported an STD in the past (χ2 = 6.10, df = 1; P < 0.05), not to have reported being HIV-positive (χ2 = 7.76, df = 1; P < 0.01), and to have lower self-efficacy for safe sex (t = 4.29, df = 664; P < 0.001). Participants who had engaged in unprotected vaginal or anal sex in the past 30 days were more likely than those who always used a condom to be younger (t = 2.41, df = 1462; P < 0.05), more likely to be married or living as married (χ2 = 69.00, df = 1; P < 0.001), less likely to report being HIV-positive (χ2 = 19.32, df = 1; P < 0.001), and more likely to be a stimulant user (χ2 = 14.17, df = 1; P < 0.001). They were also more likely to have reported needle risk behaviors, including usually or always injecting with others (χ2 = 17.48, df = 1; P < 0.001); front/back loading with a dealer (χ2 = 4.47, df = 1; P < 0.05); front/back loading with other IDUs (χ2 = 4.04, df = 1; P < 0.05); and sharing cotton, cooker, or water (χ2 = 7.12, df = 1; P < 0.01). Those engaging in unprotected sex also had lower self-efficacy for safe sex than did those who always used a condom (t = 9.70, df = 1460; P < 0.001).

Participants who had sex with an IDU partner in the past 30 days were more likely than those who did not have an IDU sex partner to be female (χ2 = 111.74, df = 1; P < 0.001), to be married or living as married (χ2 = 43.98, df = 1; P < 0.001), to have reported a prior STD (χ2 = 4.82, df = 1; P < 0.05), to report that they were HIV-positive (χ2 = 4.22, df = 1; P < 0.05), to inject more frequently (t = −3.24, df = 1237; P < 0.01), and to be a stimulant injector (χ2 = 27.47, df = 1; P < 0.001). They also were more likely to engage in risky needle use behaviors, including usually or always injecting with others (χ2 = 23.96, df = 1; P < 0.001); front/back loading with a dealer (χ2 = 3.99, df = 1; P < 0.001); using a common drug container (χ2 = 5.54, df = 1; P < 0.05); front or back loading with others (χ2 = 18.03, df = 1; P < 0.001); using a dirty needle and/or syringe (χ2 = 8.31, df = 1; P < 0.01); and sharing cotton, cooker, or water (χ2 = 11.14, df = 1; P < 0.001). They were also less likely to consider themselves a safe injector most or all of the times they injected (χ2 = 9.48, df = 1; P < 0.01). Participants who had sex with a partner who was HIV-positive or whose HIV status they did not know were more likely to be older (t = −3.10, df = 1547; P < 0.01), to have had an STD (χ2 = 12.10, df = 1; P < 0.001), to be HIV-positive (χ2 = 42.54, df = 1; P < 0.001), not to consider themselves a safe injector most or all the time (χ2 = 22.87, df = 1; P < 0.001), and to have lower safe sex self-efficacy (t = 3.65, df = 1050; P < 0.001).

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Multiple Logistic Regression Analyses of Sex Risks

Table 3 shows the results of the logistic regressions for the 4 high-risk sex behaviors. Gender was a significant predictor with each behavior, except for sex with an HIV-positive partner (or with a partner of unknown HIV status). Men were at greater risk for having multiple partners (OR = 2.32, 95% CI: 1.64 to 3.27), whereas women were at higher risk for unsafe vaginal or anal sex (OR = 0.61, 95% CI: 0.46 to 0.81) and sex with an IDU (OR = 0.26, 95% CI: 0.20 to 0.35). Respondents having multiple partners were also younger (OR = 0.97, 95% CI: 0.96 to 0.99), less likely to be married or living as married (OR = 0.39, 95% CI: 0.28 to 0.53), more likely to have had an STD (OR = 1.40, 95% CI: 1.07 to 1.83), less likely to be HIV-positive (OR = 0.60, 95% CI: 0.39 to 0.93), more likely to be a stimulant injector (OR = 1.44, 95% CI: 1.07 to 1.93), more likely to front/back load with a dealer (OR = 1.35, 95% CI: 1.02 to 1.79), and more likely to have lower safe sex self-efficacy (OR = 0.73, 95% CI: 0.58 to 0.92). Respondents having unsafe vaginal or anal sex were less likely to be from Kiev (OR = 0.50, 95% CI: 0.36 to 0.70) or Odessa (OR = 0.40, 95% CI: 0.28 to 0.57), more likely to be married or living as married (OR = 3.38, 95% CI: 2.57 to 4.43), not as likely to be HIV-positive (OR = 0.60, 95% CI: 0.41 to 0.88), less likely to consider themselves safe injectors (OR = 0.74, 95% CI: 0.56 to 0.98), and more likely to have lower safe sex self-efficacy (OR = 0.30, 95% CI: 0.24 to 0.39). Those having sex with an IDU were more likely to be from Odessa (OR = 1.51, 95% CI: 1.06 to 2.17), to be female (OR = 0.26, 95% CI: 0.20 to 0.35), to be older (OR = 1.02, 95% CI: 1.00 to 1.04), to be married or living as married (OR = 1.88, 95% CI: 1.45 to 2.44), to inject more frequently (OR = 1.01, 95% CI: 1.00 to 1.01), to inject stimulants (OR = 1.91, 95% CI: 1.44 to 2.54) and to inject with others most or all the time (OR = 1.59, 95% CI: 1.20 to 2.10). Those who had sex with a partner who was HIV-positive or someone of unknown HIV status were more likely to be from Odessa (OR = 2.54, 95% CI: 1.80 to 3.59), not to be married or living as married (OR = 0.73, 95% CI: 0.56 to 0.94), to have had an STD (OR = 1.38, 95% CI: 1.08 to 1.77), to report that they were HIV-positive (OR = 2.07, 95% CI: 1.44 to 2.96), and to have lower safe sex self-efficacy (OR = 0.74, 95% CI: 0.59 to 0.92). All ORs were statistically significant at P < 0.05 or greater.

Table 3
Table 3
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DISCUSSION

A number of noteworthy findings emerged from this study. First, most IDUs who participated were sexually active, with approximately 80% of both genders reporting sexual activity in the past 30 days, and at high risk in their sex- and injection-related behaviors. Overall, more than a quarter (27%) of the sample had sex with multiple partners, 53% had vaginal or anal sex without a condom, 41% reported that their sex partner was also an IDU, and 37% had an HIV-infected sex partner or a partner whose HIV status was unknown. Research suggests that sexual transmission of HIV among IDUs is of increasing importance in Ukraine24 and the United States25-28 and that most IDUs are sexually active,29,30 including those who are HIV-seropositive.31 Second, women may be at greater overall risk for HIV infection than men because they were more likely to have had unprotected vaginal or anal sex and sex with another IDU. These findings were hypothesized, although unprotected sex among women in this study was more prevalent than that observed elsewhere,8,9 as was sex with an IDU partner.12,32 Not surprisingly, women were also more likely to have been told that they were HIV-positive. Serology results from this study also indicated that more women (40%) than men (32%) were infected,33 a trend similar to that in the United States.34 The finding that only 36% of the participants in the study knew they were infected calls for increased HIV testing and counseling.

Third, several injection-related risk behaviors were associated with sex-related risk behaviors. Stimulant injectors were more likely to have reported multiple sex partners and sex with another IDU. Participants reporting multiple sex partners were also more likely to have front/back loaded with a dealer. Others have noted the relation between stimulant use and HIV risk and the decrease in HIV risk with corresponding reductions in stimulant use.35 Fourth, the association observed between a history of STDs and having sex with multiple partners over a 30-day period and/or having sex with an HIV infected partner or a partner with unknown HIV status indicates a troubling situation. The relation between STDs and the sexual transmission of HIV is well documented.36-38 The finding that IDUs in this study with prior STDs were active sexually and with partners of high risk portends the continued expansion of the epidemic through needle and sex-related risks.

There are several limitations to this study that should be considered. First, the sampling plan was designed to access IDUs throughout each city, based on outreach workers' knowledge of congregation sites, to generate findings representative of drug injectors in those locations. Although this approach is preferable to convenience sampling, it is not known how representative the samples were of IDUs in each city. Because of the nature of recruitment, it is not possible to know the precise number of IDUs who refused to participate; however, outreach workers reported few refusals. Nevertheless, the sample likely overrepresents IDUs willing to spend the time necessary to participate in the research and motivated by the modest stipend. Thus, this study does not profess to generalize to all IDUs but only to a relatively representative street-recruited sample that is likely more impoverished and in worse health than other drug users in Ukraine. Second, the data reported here were based on self-report, which potentially could be biased because of recall errors and social desirability. Because of the relatively brief period respondents were asked to remember (ie, 30 days), recall error should have been minimized. It is unclear what influence social desirability might have had in the study, because IDUs in Ukraine are far less familiar with research practices than IDUs in the United States and elsewhere. Although social desirability cannot be ruled out as a factor, it is unlikely that the main findings were affected. Moreover, previous studies have found that drug users' self-reports are sufficiently valid for this type of research.39,40

The exponential growth of injection drug use and the HIV epidemic in Ukraine after the disintegration of the Soviet Union, combined with the lack of public health resources to address these problems, signifies a grim situation. In the Russian Federation and Ukraine, fewer than 24,000 of those infected were receiving antiretroviral treatment as of mid-2006.41 HIV diagnoses have more than doubled annually since 2000,15 with, alarmingly, nearly a third of new cases occurring among those aged 15 to 24 years.42 The epidemic continues to increase among IDUs and, more recently, among women.16,32 There is little that is currently being done to change these conditions. Given the poor economic situation, lack of adequate health care, and indifference of officials to the problems of drug use and HIV, there is no cause for optimism. Ukraine IDUs' perceived lack of self-worth, in combination with their chronic addiction, offers little hope of them changing on their own. HIV has an impact not only on those directly affected through drug use or HIV but on the society, because the economic and social conditions in Ukraine are not likely to improve until there is help for its most marginalized and disenfranchised citizens. Interventions have been shown to reduce injection- and sex-related risk behaviors.43-45 In light of the study's findings that low self-efficacy for practicing safe sex was associated with 3 of the 4 sex risk factors, including sex with multiple partners, unprotected vaginal or anal sex, and sex with an HIV-infected partner or someone of unknown HIV status, interventions should address improving safe sex self-efficacy.

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ACKNOWLEDGMENTS

The authors acknowledge the dedicated NGO staff and directors who participated in this project. These include Elena Teryayeva with Health of Nation in Makeevka/Donetsk; Olga Kostyuk with Faith, Hope and Love in Odessa; and Natalya Podlesnaya with the Substance Abuse and AIDS Prevention Foundation in Kiev. Their commitment to preventing the further spread of HIV in their country is nothing less than heroic. The authors are indebted to the drug users who agreed to participate and gave their time, permitting us to conduct this research.

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REFERENCES

1. Ministry of Health Ukraine, Ukrainian AIDS Centre, World Health Organization, International HIV/AIDS Alliance in Ukraine, United National Program for HIV/AIDS, Geneva, Switzerland. Report on the National Consensus Estimates on HIV and AIDS in Ukraine as of End of 2005. Kiev, Ukraine; 2006.

2. Khodakevich L, Dehne KL. HIV Epidemics in Drug-Using Population and Increasing Drug Use in Central and Eastern Europe. National Institute on Drug Abuse, U.S. Department of Health and Human Services, Bethesda, MD. Global Research Network on HIV Prevention in Drug-Using Populations: Inaugural Meeting Report. Geneva, Switzerland; 1998.

3. World Health Organization. The current global situation of the HIV/AIDS pandemic. Wkly Epidemiol Rec. 1995;70:355.

4. Barnett T, Whiteside A, Khodakevich L, et al. The HIV/AIDS epidemic in Ukraine: its potential and social impact. Soc Sci Med. 2000;51:1387-1403.

5. Hamers FF, Batter V, Downs AM, et al. The HIV epidemic associated with injection drug use in Europe: geographic and time trends. AIDS. 1997;11:1365-1374.

6. Ministry of Health, Ukraine, Ukrainian AIDS Centre, L.V. Gromashevskogo Institute of Epidemiology, Central Sanitary Epidemiological Station of the Ministry of Health of Ukraine. HIV-Infection in Ukraine: Information Bulletin No. 26. Ministry of Health, Kiev, Ukraine; 2006.

7. Scherbinska A. HIV infection in Ukraine: a review of epidemiological data [abstract CDC0398]. Presented at: XVI International AIDS Conference; 2006; Toronto.

8. Gollub EL, Rey D, Obadia Y, et al. Gender differences in risk behaviors among HIV+ persons with an IDU history: the link between partner characteristics and women's higher drug-sex risks. Sex Transm Dis. 1998;25:483-488.

9. Bouhnik A-D, Preau M, Lert F, et al. Unsafe sex in regular partnerships among heterosexual persons living with HIV: evidence from a large representative sample of individuals attending outpatient services in France. AIDS. 2007;(Suppl 1):S57-S62.

10. Lollis CM, Strothers HS, Chitwood DD, et al. Sex, drugs, and HIV: does methadone maintenance reduce drug use and risk sexual behavior? J Behav Med. 2000;23:545-557.

11. Booth RE. Gender differences in high-risk sex behaviors among heterosexual drug injectors and crack smokers. Am J Drug Alcohol Abuse. 1995;21:419-432.

12. Booth RE, Koester SK, Pinto F. Gender differences in sex-risk behaviors, economic livelihood, and self-concept among drug injectors and crack smokers. Am J Addict. 1995;4:313-322.

13. DesJarlais DC, Friedman SR, Goldsmith D, et al. Heterosexual transmission of human immunodeficiency virus from intravenous drug users: regular partnerships and prostitution. In: Voeller B, Reinish JM, Gottleib M, eds. AIDS and Sex. New York: Oxford University Press; 1990:245-256.

14. Booth RE. HIV and HCV risk reduction interventions in drug detoxification and treatment setting. Presented at: 68th Annual Scientific Meeting of the College on Problems of Drug Dependence; 2006; Scottsdale.

15. Vidal-Trecan G, Coste J, Delamare N, et al. Female intravenous drug users: do they take more HIV and HCV risks than men? Presented at: Eighth International Conference on the Reduction of Drug Related Harm; 1997; Paris.

16. Wiebel WW, Levin LB. The Indigenous Leader Outreach Model: Intervention Manual. AIDS Outreach Demonstration Project. Chicago, IL: School of Public Health, University of Illinois at Chicago; 1993.

17. Carlson RG, Wang J, Siegal HA, et al. An ethnographic approach to targeted sampling: problems and solutions in AIDS prevention research among injection drug and crack-cocaine users. Hum Organ. 1994;53:279-286.

18. Booth RE, Wiebel W. The effectiveness of reducing needle related risks for HIV through indigenous outreach to injection drug users. Am J Addict. 1992;1:277-287.

19. Booth RE, Kennedy JK, Brewster JT, et al. Drug injectors and dealers in Odessa, Ukraine. J Psychoactive Drugs. 2003;35:419-426.

20. Weatherby NL, Needle R, Cesari H, et al. Validity of self-reported drug use among injection drug users and crack smokers recruited through street outreach. Eval Program Plann. 1994;17:347-355.

21. Dowling-Guyer S, Johnson ME, Fisher DG, et al. Reliability of drug users' self-reported HIV risk behaviors and validity of self-reported recent drug use. Assessment. 1994;1:383-392.

22. Carey MP, Morrison-Beedy D, Johnson BT. The HIV-knowledge questionnaire: development and evaluation of a reliable, valid and practical self-administered questionnaire. AIDS Behav. 1997;1:61-74.

23. SAS Institute. SAS/STAT Users Guide, Version 9.1 [computer program]. Cary, NC: SAS Institute; 2003.

24. Hamers FF, Downs AM. HIV in Central and Eastern Europe. Lancet. 2003;361:1035-1044.

25. Kral AH, Bluthenthal RN, Lorvick J, et al. Sexual transmission of HIV-1 among injection drug users in San Francisco, USA: risk-factor analysis. Lancet. 2001;357:1397-1401.

26. Strathdee S, Galai N, Safaeian M, et al. Sex differences in risk factors for HIV seroconversion among injection drug users: a 10-year perspective. Arch Gen Psychiatry. 2001;161:1281-1288.

27. Des Jarlais DC, Perlis T, Arasteh K, et al. HIV incidence among injection drug users in New York City 1990 to 2002: use of serologic test algorithm to assess expansion of HIV prevention services. Am J Public Health. 2005;95:1439-1444.

28. Strathdee SA, Sherman SG. The role of sexual transmission of HIV infection among injection and non-injection drug users. J Urban Health. 2003;80:iii7-iii14.

29. Rhodes T, Sarang A, Bobrik A, et al. HIV transmission and HIV prevention associated with injecting drug use in the Russian Federation. Intern J Drug Policy. 2004;15:1-16.

30. Des Jarlais DC, Chamberland ME, Yancovitz SR, et al. Heterosexual partners: a large risk group for AIDS. Lancet. 1984;2:1346-1347.

31. Panda S, Chatterjee A, Battacharya SK, et al. Transmission of HIV from injecting drug users to their wives in India. Int J STD AIDS. 2000;7:468-473.

32. Booth RE, Watters JK, Chitwood DD. The prevalence of HIV risk related sex behaviors among injection drug users, crack smokers, and injection drug users who smoke crack. Am J Public Health. 1993;83:1144-1149.

33. Booth RE, Kwiatkowski CF, Brewster JT, et al. Predictors of HIV sero-status among drug injectors in three Ukraine sites. AIDS. 2006;20:1-7.

34. Espinoza L, Hall HI, Hardnett F, et al. Characteristics of persons with heterosexually acquired HIV infection, United States 1999-2004. Am J Public Health. 2007;97:144-149.

35. Woody GE, Gallop R, Luborsky L, et al, for the Cocaine Psychotherapy Study Group. HIV risk reduction in the National Institute on Drug Abuse Cocaine Collaborative Treatment Study. J Acquir Immune Defic Syndr. 2003;33:82-87.

36. White RG, Orroth KK, Kornromp EL, et al. Can population differences explain the contrasting results of the Mwanza, Rakai, and Masaka HIV/sexually transmitted disease intervention trials? A modeling study. J Acquir Immune Defic Syndr. 2004;37:1500-1513.

37. Gray R, Wawer M, Sewankambo N, et al. Relative risk and population attributable fraction of incident HIV associated with symptoms of sexually transmitted diseases in Rakai District, Uganda. Rakai Project Team. AIDS. 1999;13:2113-2123.

38. Freeman EE, Weiss HA, Glynn JR, et al. Herpes simplex virus 2 infection increases HIV acquisition in men and women: systematic review and meta-analysis of longitudinal studies. AIDS. 2006;20:73-83.

39. Maisto S, McKay J, Conners G. Self-reported issues in substance abuse: state of the art and future directions. Behav Assess. 1990;121:117-134.

40. Booth RE, Crowley TJ, Zhang Y. Substance abuse treatment entry, retention, and effectiveness: out-of-treatment opiate injection drug users. Drug Alcohol Depend. 1996;42:11-20.

41. World Health Organization/United Nations Program on HIV/AIDS. Progress in Scaling Up Access to HIV Treatment in Low- and Middle Income Countries, June 2006 Fact Sheet. Geneva, Switzerland: WHO/UNAIDS; 2006.

42. EuroHIV. HIV/AIDS Surveillance in Europe: End-Year Report 2005. No. 73. Saint-Maurice, France; Institute de Veille Sanitaire; 2006.

43. Booth RE, Watters JK. How effective are risk-reduction interventions targeting injection drug users? A critical review of published studies. AIDS. 1994;8:1515-1524.

44. Semann S, Des Jarlais DC, Sogolow E, et al. A meta-analysis of the effect of HIV prevention interventions on the sex behaviors of drug users in the United States. J Acquir Immune Defic Syndr. 2002;30(Suppl):S73-S93.

45. Kwiatkowski CF, Stober DR, Booth RE, et al. Predictors of condom use following HIV intervention with heterosexually active drug users. Drug Alcohol Depend. 1999;54:57-62.

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Interventions with injection drug users in Ukraine
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Addiction, 104(): 1864-1873.
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Journal of Womens Health
Gender Differences in HIV Risk Behaviors of Inmates
Abiona, TC; Adefuye, AS; Balogun, JA; Sloan, PE
Journal of Womens Health, 18(1): 65-71.
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AIDS
New challenges for mathematical and statistical modeling of HIV and hepatitis C virus in injecting drug users
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Keywords:

HIV; injection drug use; sex risk behaviors; Ukraine

© 2007 Lippincott Williams & Wilkins, Inc.

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